That mentality remains today, as businesses continue to allocate funds to programs because they are considered a “standard” part of a marketing plan — regardless of whether they are performing or not.

With marketing now responsible for customer lifetime value, minimizing the cost of customer acquisition and engagement is the key to achieving desired business objectives. The only way to do that is to continually optimize the marketing mix to ensure that each program is individually delivering the best results, and jettisoning those that don't (even if it is perceived as an “untouchable” program). Hanging on to non-performing channels can be disastrous.

Set Your Standards

Establishing a formal benchmarking model is critical, but can be daunting in a start-up environment where you have a blank slate and no history.

Take a deep breath, and start with stake-in-the-ground objectives related to cost of acquisition and engagement. The easiest way to get there is with a hypothesis of the lifetime revenue value of the customer (how much they will pay you in total over time) and then back into some acquisition and engagement numbers (what will it cost you to acquire and support this customer) that lead to the desired profit margin.

Once you have these stakes, you can model your marketing budget and map desired results. You can find benchmark data with a little bit of Internet research and don't forget to tap into your personal network of peers.

MarketingProfs and Smart Insights are great sources for industry benchmark information as are some of what I refer to as MarTech "Ecosystem Suns" — companies like Hubspot, Marketo and IBM/SilverPop — which curate their own MarTech ecosystems and contribute to general industry knowledge. And, don’t forget to ask your tool vendors — every tool company should be willing to stand up and tell you what to expect in terms of results.

Once armed with some initial benchmark goals, the next step is to create a budget model that incorporates all the data points you need to track program efficacy. For example: if you were an e-commerce company using a number of programs to drive traffic to your site, you would be looking at:

Traffic

Conversion to sale

Average order value

Cost to acquire

Lifetime order value

If you're unable to slog through this yourself, there are specialists such as Mix3 Metrics ready to help. In the example above, cohort analysis by program is very important since the program with the lowest cost of acquisition may not ultimately yield the largest lifetime order value. It will take time to gather cohort data but once you have it, it’s the secret to optimizing lifetime value.

Track, Test and Reiterate

With a basic model and set of hypotheses in hand, you can begin to track and benchmark results.

You have two choices for programs that don’t perform as expected — eliminate them or adjust and try again. Over time your hypotheses will improve and you should see results closer to what you predict. Once you have a baseline of programs you understand and can reasonably predict, you have the perfect environment to test new programs and tools. With thousands of marketing tools to choose from, you should be experimenting all the time.

Of course all of this effort is complicated by the fact that programs frequently don’t work in isolation and the net effect of using three or four in tandem often makes the difference. Tools like Kvantum help marketers quantify the cross-channel impact of multiple programs, and understand the value and impact of offline and social channels where it is not easy to quantify program results.

There are a host of tools such as Allocadia and Bizible available to also help marketers track the performance of their marketing activities in an integrated way. These may be a bit expensive for startups with a limited number of programs and virtually no budget, but they are essential for larger, established companies with bigger teams, a broad set of programs in play at any one time, and a geographically dispersed organization.

Creating a benchmark-based marketing model takes time and energy, but once in place it becomes easier and easier to refine the model and spend to achieve optimum impact.

About the Author

Anita Brearton is Founder/CEO and Co-CMO of CabinetM, a marketing technology discovery and management platform that helps marketing teams manage the technology they have, and find the technology they need. Anita is a long time tech start-up marketer and has had the great fortune of driving marketing programs through the early stages of a startup all the way to IPO and acquisition.

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